Explainable ai: A review of machine learning interpretability methods

P Linardatos, V Papastefanopoulos, S Kotsiantis - Entropy, 2020‏ - mdpi.com
Recent advances in artificial intelligence (AI) have led to its widespread industrial adoption,
with machine learning systems demonstrating superhuman performance in a significant …

–Omic and electronic health record big data analytics for precision medicine

PY Wu, CW Cheng, CD Kaddi… - IEEE Transactions …, 2016‏ - ieeexplore.ieee.org
Objective: Rapid advances of high-throughput technologies and wide adoption of electronic
health records (EHRs) have led to fast accumulation of–omic and EHR data. These …

[HTML][HTML] Machine learning of neuroimaging for assisted diagnosis of cognitive impairment and dementia: a systematic review

E Pellegrini, L Ballerini, MCV Hernandez… - Alzheimer's & Dementia …, 2018‏ - Elsevier
Introduction Advanced machine learning methods might help to identify dementia risk from
neuroimaging, but their accuracy to date is unclear. Methods We systematically reviewed the …

Machine learning in healthcare: review, opportunities and challenges

A Nayyar, L Gadhavi, N Zaman - Machine learning and the internet of …, 2021‏ - Elsevier
Abstract Machine learning technology is a prominent research field aiming to build a system
which imitates human intelligence. Machine learning can be applied in the healthcare …

Privft: Private and fast text classification with homomorphic encryption

A Al Badawi, L Hoang, CF Mun, K Laine… - IEEE Access, 2020‏ - ieeexplore.ieee.org
We present an efficient and non-interactive method for Text Classification while preserving
the privacy of the content using Fully Homomorphic Encryption (FHE). Our solution (named …

Artificial intelligence for internet of things and enhanced medical systems

S Oniani, G Marques, S Barnovi, IM Pires… - Bio-inspired …, 2020‏ - Springer
Abstract Internet of things (IoT), Big Data, and artificial intelligence (AI) are related research
fields that have a relevant impact factor on the design and development of enhanced …

[HTML][HTML] Convolution neural network–based Alzheimer's disease classification using hybrid enhanced independent component analysis based segmented gray matter …

S Basheera, MSS Ram - Alzheimer's & Dementia: Translational Research & …, 2019‏ - Elsevier
In recent times, accurate and early diagnosis of Alzheimer's disease (AD) plays a vital role in
patient care and further treatment. Predicting AD from mild cognitive impairment (MCI) and …

Deep Neural Network Based Ensemble learning Algorithms for the healthcare system (diagnosis of chronic diseases)

J Abdollahi, B Nouri-Moghaddam… - arxiv preprint arxiv …, 2021‏ - arxiv.org
learning algorithms. In this paper, we review the classification algorithms used in the health
care system (chronic diseases) and present the neural network-based Ensemble learning …

[ספר][B] Industrial applications of machine learning

P Larrañaga, D Atienza, J Diaz-Rozo, A Ogbechie… - 2018‏ - taylorfrancis.com
Industrial Applications of Machine Learning shows how machine learning can be applied to
address real-world problems in the fourth industrial revolution, and provides the required …

Application of Gabor wavelet and Locality Sensitive Discriminant Analysis for automated identification of breast cancer using digitized mammogram images

U Raghavendra, UR Acharya, H Fujita, A Gudigar… - Applied Soft …, 2016‏ - Elsevier
Breast cancer is one of the prime causes of death in women. Early detection may help to
improve the survival rate to a great extent. Mammography is considered as one of the most …